GPS /DR positioning using Kalman filter has a large margin of error after a period of time
even divergent. This paper uses wavelet neural network in the Kalman filter to adjust the noise covariance matrix. Simulation results of mobile robot GPS/DR positioning system show that the divergence can effectively suppress
and can effectively improve the positioning accuracy.